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Advanced Microwave Sensors and Their Applications in Measurement
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Advanced Microwave Sensors and Their Applications in Measurement

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Electronic Sensors".

Deadline for manuscript submissions: 20 September 2025 | Viewed by 5459

Special Issue Editor

Prof. Dr. Changjun Liu

E-Mail Website
Guest Editor
School of Electronics and Information Engineering, Sichuan University, Chengdu 610064, China
Interests: microwave wireless power transmission; microwave circuits; antennas; permittivity measurement; microwave biomedical applications

Special Issue Information

Dear Colleagues,

Sensors have undoubtedly become an essential part of the modern world. Sensors, as key tools for capturing changes in physical, chemical, or biological parameters, greatly expand their range of applications and performance when combined with microwave technology. Microwave sensors are widely used in fields such as radar and aerospace, automotive safety, industrial automation, communication systems, health and safety monitoring, environmental monitoring, and agriculture. One application of microwave energy is wireless power transmission, which involves transmitting energy wirelessly through microwaves. There is a close relationship between microwave measurement and wireless power transfer. In wireless power transfer, the generation, transmission, reception, and conversion of microwaves involve precise microwave measurement to ensure the efficiency and safety of energy transmission.

The non-contact measurement capabilities, high precision and sensitivity, powerful penetration, and adaptability to harsh environmental conditions of microwave sensors demonstrate their tremendous advantages in various application scenarios. This Special Issue aims to delve into the development and applications of microwave sensors, and we invite authors to submit high-quality manuscripts to advance the progress of microwave sensors in the measurement field. The themes of microwave energy applications in production and life include, but are not limited to, the following:

Wireless power supply for sensors;

Real-time monitoring of environmental conditions, including air, water, and soil pollution, by microwave sensors;

Sustainable green agriculture monitoring and power supply;

Process monitoring in drying and heating fields;

Real-time microwave sensors in biomedicine;

Microwave power transmission and monitoring on the Internet of Things (IoT);

New applications of real-time microwave sensing systems;

Electromagnetic materials and microwave measurement principles

Real-time monitoring in industrial production.

Prof. Dr. Changjun Liu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • microwave energy applications in the industry
  • microwave sensors and advanced sensing systems
  • real-time industrial monitoring
  • sensor performance benchmarking: simulation vs. validation
  • permittivity measurement sensor
  • emerging wireless sensor

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Published Papers (5 papers)

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Research

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13 pages, 4506 KiB  
Article
A High-Temperature and Wide-Permittivity Range Measurement System Based on Ridge Waveguide
by Rui Xiong, Yuanhang Hu, Anqi Xia, Kama Huang, Liping Yan and Qian Chen
Sensors 2025, 25(2), 541; https://doi.org/10.3390/s25020541 - 18 Jan 2025
Viewed by 443
Abstract
Potential applications of microwave energy, a developed form of clean energy, are diverse and extensive. To expand the applications of microwave heating in the metallurgical field, it is essential to obtain the permittivity of ores throughout the heating process. This paper presents the [...] Read more.
Potential applications of microwave energy, a developed form of clean energy, are diverse and extensive. To expand the applications of microwave heating in the metallurgical field, it is essential to obtain the permittivity of ores throughout the heating process. This paper presents the design of a 2.45 GHz ridge waveguide apparatus based on the transmission/reflection method to measure permittivity, which constitutes a system capable of measuring the complex relative permittivity of the material under test with a wide temperature range from room temperature up to 1100 °C. The experimental results indicate that the system is capable of performing rapid measurements during the heating process. Furthermore, the system is capable of accurately measuring dielectric properties when the real part of the permittivity and the loss tangent vary widely. This measurement system is suitable for high-temperature dielectric property measurements and has potential applications in microwave-assisted metallurgy. Full article
(This article belongs to the Special Issue Advanced Microwave Sensors and Their Applications in Measurement)
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14 pages, 3768 KiB  
Article
High-Precision Photonics-Assisted Two-Step Microwave Frequency Measurement Combining Time and Power Mapping Method
by Zhangyi Yang, Zuoheng Liu, Yuqing Jiang, Hanbo Liu, Jiaqi Li and Wei Dong
Sensors 2024, 24(19), 6415; https://doi.org/10.3390/s24196415 - 3 Oct 2024
Viewed by 946
Abstract
Photonics-assisted methods for microwave frequency measurement (MFM) show great potential for overcoming electronic bottlenecks and offer promising applications in radar and communication due to their wide bandwidth and immunity to electromagnetic interference. In common photonics-assisted MFM methods, the frequency-to-time mapping (FTTM) method has [...] Read more.
Photonics-assisted methods for microwave frequency measurement (MFM) show great potential for overcoming electronic bottlenecks and offer promising applications in radar and communication due to their wide bandwidth and immunity to electromagnetic interference. In common photonics-assisted MFM methods, the frequency-to-time mapping (FTTM) method has the capability to measure various types of signals, but with a trade-off between measurement error, measurement range, and real-time performance, while the frequency-to-power mapping (FTPM) method offers low measurement error but faces great difficulty in measuring signal types other than single-tone signals. In this paper, a two-step high-precision MFM method based on the combination of FTTM and FTPM is proposed, which balances real-time performance with measurement precision and resolution compared with other similar works based on the FTTM method. By utilizing high-speed optical sweeping and an optical filter based on stimulated Brillouin scattering (SBS), FTTM is accomplished, enabling the rough identification of multiple different signals. Next, based on the results from the previous step, more precise measurement results can be calculated from several additional sampling points according to the FTPM principle. The demonstration system can perform optical sweeping at a speed of 20 GHz/μs in the measurement range of 1–18 GHz, with a measurement error of less than 10 MHz and a frequency resolution of 40 MHz. Full article
(This article belongs to the Special Issue Advanced Microwave Sensors and Their Applications in Measurement)
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24 pages, 7984 KiB  
Article
Design and Implementation of an Ultra-Wideband Water Immersion Antenna for Underwater Ultrasonic Sensing in Microwave-Induced Thermoacoustic Tomography
by Feifei Tan and Haishi Wang
Sensors 2024, 24(19), 6311; https://doi.org/10.3390/s24196311 - 29 Sep 2024
Viewed by 799
Abstract
Microwave-induced thermoacoustic tomography (MITAT) holds significant promise in biomedical applications. It creates images using ultrasonic sensors to detect thermoacoustic signals induced by microwaves. The key to generating thermoacoustic signals that accurately reflect the fact is to achieve sufficient and uniform microwave power absorption [...] Read more.
Microwave-induced thermoacoustic tomography (MITAT) holds significant promise in biomedical applications. It creates images using ultrasonic sensors to detect thermoacoustic signals induced by microwaves. The key to generating thermoacoustic signals that accurately reflect the fact is to achieve sufficient and uniform microwave power absorption of the testing target, which is closely tied to the microwave illumination provided by the antenna. In this article, we introduce a novel design and implementation of an ultra-wideband water immersion antenna for an MITAT system. We analyze and compare the advantages of selecting water as the background medium. Simulations are conducted to analyze the ultra-wideband characteristics in impedance matching, axial ratio, and radiation pattern of the proposed antenna. The measured |S11| shows good agreement with the simulated results. We also simulate the microwave power absorption of tumor and brain tissue, and the uniform microwave power absorption and high contrast between the tumor and brain indicate the excellent performance of the proposed antenna in the MITAT system. Full article
(This article belongs to the Special Issue Advanced Microwave Sensors and Their Applications in Measurement)
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15 pages, 5540 KiB  
Article
Mobile Network Coverage Prediction Using Multi-Modal Model Based on Deep Neural Networks and Semantic Segmentation
by Sheng Zeng, Yuhang Ji, Weiwei Chen, Liping Yan and Xiang Zhao
Sensors 2024, 24(16), 5178; https://doi.org/10.3390/s24165178 - 10 Aug 2024
Cited by 1 | Viewed by 1685
Abstract
A coverage prediction model helps network operators find coverage gaps, plan base station locations, evaluate quality of service, and build radio maps for spectrum sharing, interference management, localization, etc. Existing coverage prediction models rely on the height and transmission power of the base [...] Read more.
A coverage prediction model helps network operators find coverage gaps, plan base station locations, evaluate quality of service, and build radio maps for spectrum sharing, interference management, localization, etc. Existing coverage prediction models rely on the height and transmission power of the base station, or the assistance of a path loss model. All of these increase the complexity of large-scale coverage predictions. In this paper, we propose a multi-modal model, DNN-SS, which combines a DNN (deep neural network) and SS (semantic segmentation) to perform coverage prediction for mobile networks. Firstly, DNN-SS filters the samples with a geospatial-temporal moving average filter algorithm, and then uses a DNN to extract numerical features. Secondly, a pre-trained model is used to perform semantic segmentation of satellite images of the measurement area. Thirdly, a DNN is used to extract features from the results after semantic segmentation to form environmental features. Finally, the prediction model is trained on the dataset consisting of numerical features and environmental features. The experimental results on campus show that for random location prediction, the model achieves a RMSE (Root Mean Square Error) of 1.97 dB and a MAE (Mean Absolute Error) of 1.41 dB, which is an improvement of 10.86% and 10.2%, respectively, compared with existing models. For the prediction of a test area, the RMSE and MAE of the model are 4.32 dB and 3.45 dB, respectively, and the RMSE is only 0.22 dB lower than that of existing models. However, the DNN-SS model does not need the height, transmission power, and antenna gain of the base station, or a path loss model, which makes it more suitable for large-scale coverage prediction. Full article
(This article belongs to the Special Issue Advanced Microwave Sensors and Their Applications in Measurement)
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Review

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23 pages, 9811 KiB  
Review
Microwave Sensors and Their Applications in Permittivity Measurement
by Changjun Liu, Chongwei Liao, Yujie Peng, Weixin Zhang, Bo Wu and Peixiang Yang
Sensors 2024, 24(23), 7696; https://doi.org/10.3390/s24237696 - 1 Dec 2024
Cited by 1 | Viewed by 1098
Abstract
This paper reviews microwave sensors and their applications in permittivity measurement. The detection, diagnosis, classification, and monitoring without contact and invasion have been the subject of numerous studies based on permittivity characteristics tracking. This review illustrates many new types of research in recent [...] Read more.
This paper reviews microwave sensors and their applications in permittivity measurement. The detection, diagnosis, classification, and monitoring without contact and invasion have been the subject of numerous studies based on permittivity characteristics tracking. This review illustrates many new types of research in recent years. Firstly, the application background is briefly introduced, and several main measurement methods are presented. An overview of measurement technology in various applications is compiled and summarized based on numerous typical examples. Exciting applications are compared and presented separately, combining resonator sensors with strong electric fields. Furthermore, differential signals represent trends for future applications with strong environmental immunity, an alternative option to expensive measuring equipment. With the alternation of metamaterials, microfluidics technologies, cross-technology, algorithms, and so on, sensors play an exceptionally prominent role in practical and low-cost applications. Full article
(This article belongs to the Special Issue Advanced Microwave Sensors and Their Applications in Measurement)
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